{"total":21,"rows":[{"id":"2411.05815","title":"Graph Neural Networks for Financial Fraud Detection: A Review","created":"2024-11-01","cited_by_count":25,"area":null},{"id":"2306.16384","title":"Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses","created":"2023-06-28","cited_by_count":6,"area":null},{"id":"2312.02473","title":"NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams","created":"2023-12-05","cited_by_count":6,"area":null},{"id":"2406.09675","title":"A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness","created":"2024-06-14","cited_by_count":6,"area":null},{"id":"2405.05231","title":"DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training","created":"2024-05-08","cited_by_count":5,"area":null},{"id":"2402.16731","title":"PyGim: An Efficient Graph Neural Network Library for Real Processing-In-Memory Architectures","created":"2024-02-26","cited_by_count":3,"area":null},{"id":"2303.15702","title":"Distributed Graph Embedding with Information-Oriented Random Walks","created":"2023-03-28","cited_by_count":2,"area":null},{"id":"2306.13814","title":"BatchGNN: Efficient CPU-Based Distributed GNN Training on Very Large Graphs","created":"2023-06-23","cited_by_count":2,"area":null},{"id":"2311.06837","title":"GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large Clusters","created":"2023-11-12","cited_by_count":2,"area":null},{"id":"2504.13266","title":"Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs","created":"2025-04-17","cited_by_count":2,"area":null},{"id":"2507.14570","title":"LPS-GNN : Deploying Graph Neural Networks on Graphs with 100-Billion Edges","created":"2025-07-19","cited_by_count":2,"area":null},{"id":"2406.13984","title":"Reducing Memory Contention and I/O Congestion for Disk-based GNN Training","created":"2024-06-20","cited_by_count":1,"area":null},{"id":"2407.15264","title":"LSM-GNN: Large-scale Storage-based Multi-GPU GNN Training by Optimizing Data Transfer Scheme","created":"2024-07-21","cited_by_count":1,"area":null},{"id":"2310.12403","title":"Cooperative Minibatching in Graph Neural Networks","created":"2023-10-19","cited_by_count":0,"area":null},{"id":"2512.22744","title":"Bridging Global Intent with Local Details: A Hierarchical Representation Approach for Semantic Validation in Text-to-SQL","created":"2025-12-28","cited_by_count":0,"area":null},{"id":"2601.01473","title":"Accelerating Storage-Based Training for Graph Neural Networks","created":"2026-01-04","cited_by_count":0,"area":null},{"id":"2603.06952","title":"Not All Neighbors Matter: Understanding the Impact of Graph Sparsification on GNN Pipelines","created":"2026-03-07","cited_by_count":0,"area":null},{"id":"2604.01000","title":"EmbedPart: Embedding-Driven Graph Partitioning for Scalable Graph Neural Network Training","created":"2026-04-01","cited_by_count":0,"area":null},{"id":"2606.22180","title":"FeLoG: Scalable and Efficient Distributed Graph Embedding with Feedback Loop Mechanism","created":"2026-06-20","cited_by_count":0,"area":null},{"id":"2607.17374","title":"Taurus: Accelerating Out-of-Core Graph Neural Network Inference on Billion-Scale Graphs","created":"2026-07-19","cited_by_count":0,"area":null},{"id":"2608.06441","title":"SNI-GNN: SmartNIC-Assisted Full-Graph GNN Training with In-Network Embedding Prediction","created":"2026-08-06","cited_by_count":0,"area":null}],"next_cursor":null}